No jobs
Back to Datasets

muses

DEPTH
Model: SD 2.1. Mari
Split: full
Variant: _mari_metric_ohead
Files: 333
Metrics: 14
Compare with:
absrel / median
0.2014
absrel / p90
0.6408
absrel / median
0.2005
absrel / p90
0.6389
rmse / median
2.5461
rmse / p90
13.1165
silog / mean
0.3674
silog / median
0.2025
silog / p90
0.6510
absrel / median
0.2727
absrel / p90
0.5915
rmse / median
12.3443
rmse / p90
29.6404
silog / mean
0.2895
silog / median
0.3078
silog / p90
0.7938
absrel / median
0.2005
absrel / p90
0.6240
rmse / median
3.1722
rmse / p90
13.0458
silog / mean
0.3517
silog / median
0.2072
silog / p90
0.6785
absrel / median
0.1846
absrel / p90
0.7040
rmse / median
1.3561
rmse / p90
4.7443
silog / mean
0.2211
silog / median
0.1767
silog / p90
0.5352
rmse / median
2.5610
rmse / p90
13.3995
silog / mean
0.3691
silog / median
0.2034
silog / p90
0.6568
image mean / absrel
0.3849
all / absrel
0.3844
all / delta1
0.5144
all / delta2
0.7799
all / delta3
0.8914
all / log10
0.1356
all / mae
5.8395
all / rmse
11.6032
all / rmse log
0.4236
all / silog
0.3674
all / sqrel
10.8507
image mean / delta1
0.5130
image mean / delta2
0.7781
image mean / delta3
0.8900
far / absrel
0.3447
far / delta1
0.3614
far / delta2
0.6584
far / delta3
0.8172
far / log10
0.1851
far / mae
15.3590
far / rmse
19.4632
far / rmse log
0.4900
far / silog
0.2895
far / sqrel
10.0101
image mean / log10
0.1362
image mean / mae
5.9742
mid / absrel
0.3583
mid / delta1
0.5086
mid / delta2
0.7654
mid / delta3
0.8817
mid / log10
0.1382
mid / mae
6.3446
mid / rmse
12.0932
mid / rmse log
0.4218
mid / silog
0.3517
mid / sqrel
9.9769
near / absrel
0.3962
near / delta1
0.5967
near / delta2
0.8594
near / delta3
0.9387
near / log10
0.1111
near / mae
2.7205
near / rmse
4.8771
near / rmse log
0.3343
near / silog
0.2211
near / sqrel
10.1558
image mean / rmse
11.8910
image mean / rmse log
0.4255
image mean / silog
0.3691
image mean / sqrel
10.9079
image median / absrel
0.3380
all / absrel
0.3374
all / delta1
0.5422
all / delta2
0.8236
all / delta3
0.9312
all / log10
0.1224
all / mae
5.3502
all / rmse
10.0373
all / rmse log
0.3940
all / silog
0.3498
all / sqrel
5.2819
image median / delta1
0.5384
image median / delta2
0.8211
image median / delta3
0.9303
far / absrel
0.3105
far / delta1
0.3418
far / delta2
0.7606
far / delta3
0.9356
far / log10
0.1451
far / mae
13.8940
far / rmse
17.4212
far / rmse log
0.4027
far / silog
0.2817
far / sqrel
6.9027
image median / log10
0.1225
image median / mae
5.4579
mid / absrel
0.3176
mid / delta1
0.5452
mid / delta2
0.8272
mid / delta3
0.9301
mid / log10
0.1220
mid / mae
5.6821
mid / rmse
10.5255
mid / rmse log
0.3823
mid / silog
0.3331
mid / sqrel
5.8062
near / absrel
0.2536
near / delta1
0.6785
near / delta2
0.9396
near / delta3
0.9937
near / log10
0.0930
near / mae
1.8587
near / rmse
2.8525
near / rmse log
0.2770
near / silog
0.1650
near / sqrel
1.2464
image median / rmse
10.2809
image median / rmse log
0.3943
image median / silog
0.3517
image median / sqrel
5.3422
pixel pool / absrel
0.3768
all / absrel
0.3763
all / delta1
0.5383
all / delta2
0.8024
all / delta3
0.9054
all / log10
0.1282
all / mae
5.8853
all / rmse
13.8944
all / rmse log
0.4358
all / silog
0.4354
all / sqrel
12.2795
pixel pool / delta1
0.5365
pixel pool / delta2
0.8001
pixel pool / delta3
0.9037
far / absrel
0.3319
far / delta1
0.3534
far / delta2
0.6937
far / delta3
0.8545
far / log10
0.1667
far / mae
15.6612
far / rmse
22.7660
far / rmse log
0.4992
far / silog
0.4200
far / sqrel
10.9090
pixel pool / log10
0.1290
pixel pool / mae
6.0620
mid / absrel
0.3514
mid / delta1
0.5284
mid / delta2
0.7875
mid / delta3
0.8972
mid / log10
0.1310
mid / mae
6.3473
mid / rmse
14.5979
mid / rmse log
0.4350
mid / silog
0.4337
mid / sqrel
11.1896
near / absrel
0.4406
near / delta1
0.5984
near / delta2
0.8578
near / delta3
0.9341
near / log10
0.1141
near / mae
2.8496
near / rmse
9.0382
near / rmse log
0.4235
near / silog
0.3747
near / sqrel
14.9809
pixel pool / rmse
14.3276
pixel pool / rmse log
0.4381
pixel pool / silog
0.4378
pixel pool / sqrel
12.3523
Euler View - ML Experiment Monitor